Configuration
This section describes how to configure the MSA Search NIM container using environment variables, GPU selection, and volume mounting.
GPU Selection
By default, Docker uses all available GPUs on the system when started with the NVIDIA Container Runtime:
To expose only specific GPUs to the container, use the --gpus flag:
The device IDs are listed in the output of nvidia-smi -L. For more information on GPU selection, refer to the NVIDIA Container Toolkit documentation.
Environment Variables
The following environment variables can be passed to the NIM using the -e flag with docker run:
Volumes
The following container paths can be mounted to local directories for persistent storage.
The MODEL_PATH environment variable is also supported for backward compatibility with the same behavior as NIM_MODEL_NAME.
MMseqs2 Pipeline Tuning Environment Variables
The MSA Search NIM exposes several environment variables that control internal MMseqs2 pipeline parameters. These are set at container startup and apply globally to all requests. The cascaded search pipeline (used by both colabfold and template search) follows these steps per database:
- Search — Iterative profile search to find initial hits
- Expand — Recover remote homologs similar to initial hits
- Align — Sensitive realignment of expanded candidates
- Filter — Quality filtering (for example, query coverage, and sequence identity)
- result2msa — Convert filtered results to A3M alignment
The variables below tune the align and filter steps, which directly affect per-database output depth and, consequently, the size of the merged colabfold alignment.
Align-Step Parameters
These control how many targets and alternative alignments are kept during the post-expansion realignment. Together, max_accept and alt_ali determine the upper bound U on the untrimmed per-database sequence count: U ≤ max_accept × (1 + alt_ali).
With defaults, each database can produce up to 100 × (1 + 10) = 1,100 sequences before trimming. Per-database API results are trimmed to max_msa_sequences (N, default 500), but the merged colabfold entry concatenates untrimmed results from all D databases, yielding up to D × 1,100 sequences.
Filter-Step Parameters
These control quality filtering applied after the align step. Separate variables are provided for the profile (first-database) and follow-up (subsequent database) filter steps.
Expand-Step Parameters
Search Iteration Parameters
Other Pipeline Parameters
These environment variables are global: they apply to all requests served by the NIM instance. To change them, restart the container with the desired values. A future release may expose some of these as per-request API parameters.